With the development of mobile camera technology, more and more users use mobile devices to take photos in their daily lives, and send the taken photos or pictures to friends and colleagues via a wireless network, or release them in blogs or social networks, so as to share them with friends and colleagues in time. Before releasing the photos, many users (especially female users) want to perform some facial image processing on these photos so as to obtain various effects. It imposes higher requirements on the current image processing techniques.
One challenge that the current image processing techniques face is how to automatically and precisely segment a face from an image comprising the face and surrounding areas, as a basis for further facial image processing. Segmenting a fine face region is a benefit for realizing subsequent various satisfactory image processing, such as facial image editing, effecting and the like. If some background images are introduced or some face regions are missed during the face segmentation from the image, only a coarse face segmentation region as shown in FIG. 1 will be obtained.
As shown in FIG. 1, the detected face segmentation region is surrounded by a dotted line. It can be seen from the face segmentation region surrounded by the dotted line that, due to background illumination or surrounding color's proximity when taking photos, the left side of the segmentation region comprises a small non-face region, and the right side excludes a partial face region near the left ear from the face segmentation region. Obviously, such a result of the face segmentation is coarse, and subsequent processing based on such a coarse face segmentation region usually leads to severe distortion in the resulting face image, or an unacceptable effect.
The difficulty for fine face region segmentation lies in a variety of objects in a picture, a variety of devices for photo taking and a variety of environmental illumination when photo taking. In practice, most of the current solutions are insufficient to process pictures having various facial features, such as, a picture of a white person or a black person, front view or side view, indoor or outdoor, a young person or an old person, and pictures with different definition or ambiguity. In particular, complicated and varying shooting conditions may incur unbalanced color distribution on a face, which may blur the image. This is why the face segmentation of a picture based only on a luminance cue and a skin color cue does not generate a satisfactory effect. Further, color similarity between a face region and background objects also makes it difficult to differentiate color information in segmenting the whole face region. Thus, how to obtain a reliable and fine face segmentation region becomes a primary issue in facial image processing.